Yu Lin

9.3k citations
92 papers · 4.7k indexed · 1 hit paper · h-index 22

Impact in

Papers in

    • Genomics and Phylogenetic Studies 39
    • Gene expression and cancer classification 9
    • Bioinformatics and Genomic Networks 8
    • Machine Learning in Bioinformatics 6
    • RNA and protein synthesis mechanisms 6
    • Genome Rearrangement Algorithms 19

Yu Lin

85 papers receiving 4.6k citations

Hit Papers

Assembly of long, error-prone reads using repeat graphs 2019 · 2.9k citations
2.9k0+2+4Years since publication50010001.5k2.0k2.5k

Peers

Yu Lin
Comparison fields: 5 of 159
  • Molecular Medicine 352
  • Endocrinology 302
  • Molecular Biology 2.7k
  • Ecology 975
  • Horticulture 34
Replace Jeffrey Yuan with:
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Marie‐Adèle Rajandream United Kingdom
Chen-Shan Chin United States
Yu Lin relative to Jeffrey Yuan United States Jeffrey Yuan's profile →
Citations per field
00.5×1.5×1.8×
Jeffrey Yuan · 1×
Citations per year

Countries citing papers authored by Yu Lin

Since Specialization
Citations

This map shows the geographic impact of Yu Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yu Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Lin more than expected).

Fields of papers citing papers by Yu Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yu Lin. The network helps show where Yu Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Yu Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yu Lin Line = papers co-authored together Yu Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Assembly of long, error-prone reads using repeat graphs
Hit paper breakdown →
20192927
2 2016209
3 2020157
4 2018126
5 201482
6 200374
7 201359
8 201856
9 202049
10 200347
11 201145
12 201245
13 200444
14 200339
15 200832
16 201231
17 201825
18 202325
19 200724
20 201423

About Yu Lin

Yu Lin is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Plant Science and Materials Chemistry, having authored 92 papers that have together received 4.7k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (39 papers), Genome Rearrangement Algorithms (19 papers), Chromosomal and Genetic Variations (12 papers), Algorithms and Data Compression (11 papers), Gene expression and cancer classification (9 papers), Bioinformatics and Genomic Networks (8 papers), Machine Learning in Bioinformatics (6 papers) and RNA and protein synthesis mechanisms (6 papers). The work is most often cited by research in Molecular Medicine (352 citations), Endocrinology (302 citations), Molecular Biology (2.7k citations), Ecology (975 citations) and Horticulture (34 citations). Yu Lin has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Pavel A. Pevzner, Jeffrey Yuan, Mikhail Kolmogorov, Bernard M. E. Moret, Yi Yang, Liang Qiao, Vaibhav Rajan, Yongqun He, Jijun Tang and Vijini Mallawaarachchi. Their work appears in journals such as BMC Bioinformatics, Journal of Computational Biology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Bioinformatics and BMC Genomics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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